Applicability of the Green-Ampt Infiltration Model with Shallow Boundary Conditions
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Bibliographic record
Abstract
The Green-Ampt model is an approximate analytical solution to Richards’ equation that is commonly used to simulate infiltration processes in hydrological models and land surface schemes. The Green-Ampt model assumes that neither a water table nor an impermeable layer (e.g., bedrock or a frost table) exist near the soil surface. In regional-scale applications these idealized conditions will often not be met, and it is presently unclear what implications this has for regional water resource models. This paper investigates the limiting conditions under which the Green-Ampt model is appropriate and how individual assumptions about lower boundary conditions affect the validity of the model. Guided by the comparison between the Green-Ampt model and numerical solutions to Richards’ equation, various simple revisions to the Green-Ampt model are suggested. Results demonstrate that even when the traditional assumptions are relaxed, the Green-Ampt model often still provides reasonable results for regional-scale analysis and can be amended to account for conditions for which it was not intended.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it